The use case: how BigPay deploys Feedzai
BigPay uses Feedzai's platform to consolidate its fraud and AML monitoring into a single system, replacing manual Excel-based reviews and multiple separate tools. It applies AI and machine learning for real-time transaction fraud detection and faster deployment of fraud rules.
More reported results
Figures published in Feedzai’s case study. They are not independently measured by usedby.
The Feedzai platform exhibits fast response times, with API responses typically within 400 milliseconds, ensuring seamless and efficient transaction processing.
In the customer’s words
We are impressed with the speed and efficiency of rule deployment on the Feedzai platform. This has significantly improved our ability to respond quickly to emerging threats and adapt to evolving regulatory requirements,Our partnership with Feedzai is critical in combating mule account activity. At its peak, it took weeks to respond to suspicious activity—today, that's been reduced to just hours. This speed allows us to identify emerging fraud patterns earlier.Feedzai users in Fintech & Payments
Companies in the same sector, with public evidence.
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Go straight to the source
Based on Feedzai’s published case study. We check the public evidence; the results are reported by the vendor.
feedzai.com- Source published
- Feb 25, 2025
- Last checked
- Oct 7, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 95%Checked
The figure is on the page; its label is our wording.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of BigPay.
- The publication dateChecked
Read from the page’s own metadata, never guessed.
- BigPay uses FeedzaiChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Fraud detection rates have improved significantly from a range of 80-85% to 95%. This improved performance has significantly reduced financial losses and improved customer trust.